A demand analysis for the PPACG region was conducted to provide a data-driven process that identified where bicycle and pedestrian network gaps existed, identified where projects had been proposed by local jurisdictions, and identified areas that were expected to have higher bicycle and pedestrian activity or need. These analyses show where network improvements should be considered and the places people want to go to that should connect with streets and trails that are comfortable for walking and bicycling.
Demand Analysis
The purpose of the demand analysis is to identify areas where people are likely to be and provide a framework to understand the environment for walking and bicycling. Demand is based on a set of factors that represent live, learn, work, and locations.
The demand analysis is represented by an index that is built off datasets that represent where people live, learn, work, and play. The analysis is based on measuring the time it takes for a person/employee to walk out of the parcel’s front door and into the front door at the corresponding land use in any direction. Employment and population demand is based on how many jobs or residents a person would pass during a 15-minute walk in any direction.
The demand index is composed of the following datasets:
- Walk time to nearest amenity including the following:
- School
- Hospital
- Park
- Walk Time to 5th Retail Location
- Employment within 15-minute walk
- Population within 15-minute walk
Figure 1. Demand Index
Additional specifics of the index and demand components for regional corridors from the recommendations section are provided in Appendix 3.
Existing Facilities
An analysis of the existing cycling and pedestrian facilities provides a general understanding of the coverage and type of infrastructure. The facilities are given a buffer to show the reasonable access area for the existing infrastructure.
Figure 2. Existing Facilities—Trail Network
This map represents the infrastructure available throughout the PPACG region. These facilities do not include sidewalks or a sidewalk gap analysis.
Reviewed Past Plans
The list represents the various local and regional plans that this project reviewed for projects, priorities, and standards that could be included or blended into a regional approach for this plan. Below are a few highlights from the jurisdictions that provided specific guidance for the ATP, while the full review of the documents listed can be found in Appendix 2.
- PPACG
- Regional Nonmotorized Plan
- Joint Land Use Study
- Financial Plan 2050 LRTP
- Congestion Mitigation Plan
- Tri-County Plan
- EL PASO COUNTY
- Major Transportation Corridor Plan
- Parks, Trails, Open Spaces Map
- Park assets
- Parks Master Plan (Trails)
- COLORADO SPRINGS
- Urban Trail Map
- Bike Map (four maps)
- Bike Master Plan
- State of Bicycling in Colorado Springs
- Legacy Loop Project
- Envision Shooks Run
- Parks System Master Plan
- PlanCOS
- Downtown Plan
- ConnectCOS + Active Transportation Network
- FOUNTAIN
- Parks, Trails & Open Space Map
- Parks and Trails Master Plan
- Comprehensive Plan
- GREEN MOUNTAIN FALLS
- Comprehensive Plan
- MANITOU SPRINGS
- Parks, Open Space, Trails Master Plan
- Parks and Trails Map
- Community Master Plan
- Transportation & Mobility Master Plan
- MONUMENT
- Parks, Trails, and Open Space Master Plan
- Comprehensive Plan
- PALMER LAKE
- Comprehensive Plan
- Three Mile Plan
- WOODLAND PARK
- Parks, Trails, Open Space Master Plan
- Parks, Trails and Open Space Map
- Comprehensive Plan
- CDOT & STATEWIDE
- Colorado Bicycle & Byways Map
- Colorado Trail Explorer
PPACG
The previous regional nonmotorized plan provided context for active transportation planning within the region. The image below represents the Primary Improvement Corridors identified for regional investment in that plan. Many of these corridors, shown above, continue to be regionally important in the active transportation network.
Colorado Springs & El Paso County
Colorado Springs and El Paso County have undertaken more efforts specific to active transportation, trails, and other facilities than other jurisdictions in the region. These jurisdictions have defined cross sections, trail typologies, language differences, and displayed other examples for how reviewing bodies can weigh in when discussing corridors and other recommendations identified in this plan. Colorado Springs’ example is shown below.
Figure 3. Planned Facilities – Network
This map represents the digitization of the proposed projects throughout the region, as identified in the listed plans. Jurisdiction specific maps can be found in Appendix 1.
Non-Motorized Crash Analysis
This section reviews data (2017-2021) for crashes involving pedestrians and bicyclists in the PPACG region, as reported by the PPACG Crash Dashboard.
Number of Crashes
Figure 4 indicates there are approximately twice as many pedestrian crashes as bicyclist crashes annually, which have resulted in 884 or more3 injuries and 79 fatalities over the course of five years. Bicyclist crashes appear to be trending downward, with 121, 94, 91, and 71 crashes in 2020, perhaps reflecting the fact that bicycling there has been an increase in infrastructure. At the time of this analysis the 2021 bicycle data was not available to explore whether that trend continued past the COVID-19 pandemic. Pedestrian crashes peaked in 2019 with 181. Additional data on the number of bicycle and pedestrian trips that took place each year would be needed to understand if the crash rate (i.e., crashes per bicycle trip) is going up or down.
Figure 4. Number of Bicyclist and Pedestrian Crashes (2017-2021)
Severity of Crashes
The Table 1, below, provides a summary of the bicycle and pedestrian crashes, by severity.
Table 1: Number and Severity of Bicyclist and Pedestrian Crashes (2017-2021)
| SEVERITY | BICYCLE | PEDESTRIAN | TOTAL |
|---|---|---|---|
| Fatal Injury | 12 | 67 | 79 |
| Serious Injury | 24 | 138 | 162 |
| Minor Injury | 229 | 414 | 643 |
| Non-Injury/Property Damage Only | 112 | 174 | 286 |
| Grand Total | 377 | 793 | 1,170 |
Day of Week
Pedestrian and bicyclist crashes happen throughout the week, likely indicating that people walk and bicycle for both recreational and utilitarian purposes. Collision activity appears to be lower on weekends; the lowest frequency occurs Sunday.
Month of Year
Similar to the distribution across the week, pedestrian and bicyclist crashes occur throughout the year, though the levels are somewhat lower in March and April and spike in September; both are likely caused by weather and daylight hours.
Time of Day
The crash data shows a significant peak in pedestrian crashes at the noon hour, with a more general increase in crashes reported in the afternoon and evening. The spike in noontime crashes could be caused by default data inputs when reporting.
Contributing Factors
The contributing factors for pedestrian collisions during this period were identified for only 10 percent of the collisions. This data is extremely important for the development of effective education and enforcement programs. Of the 67 fatal pedestrian crashes, only one had a contributing factor associated with it—Driver Inexperience—while all others were denoted as Unknown or No Apparent Contributing Factor. There may be opportunities to improve reporting of the contributing factors of crashes involving pedestrians or bicyclists to better understand and address safety concerns.
- More than 57 percent of both bicycle and pedestrian crashes listed the contributing factor as No Apparent Contributing Factor while another 31 percent listed the factor as Unknown.
- The most common categories for pedestrian crashes were associated with distracted driving, including Driver Preoccupied and Driver Emotionally Upset.
- The most common factor for bicyclist crashes was Driver Inexperience or Unfamiliar with Area.
| Factor | Cyclist Collisions |
|---|---|
| Driver unfamiliar with area | 8 |
| Driver preoccupied | 14 |
| Driver inexperience | 23 |
| Factor | Pedestrian Crashes |
|---|---|
| Evading law enforcement | 1 |
| Physical disability | 2 |
| Illness | 3 |
| Unfamiliar with area | 4 |
| Driver inexperience | 19 |
| Fatigue | 1 |
| Asleep at the wheel | 2 |
| Districted by passenger | 2 |
| Emotionally upset | 4 |
| Preoccupied | 26 |
Location on Roadway
As illustrated in Figure 10, pedestrian and bicyclist crash locations exhibit similar but different trends as listed below:
- Bicyclist crashes occurred overwhelmingly at intersections or were intersection-related
(70 percent), whereas 19 percent took place away from intersections, and 9 percent took place at driveways. - Pedestrian crashes occurred most at intersections (60 percent); however, 35 percent of crashes occurred at non-intersection locations (e.g., mid-block locations).
Figure 10. Location of Bicyclist and Pedestrian Crashes
| Location | Bicycle | Pedestrian |
|---|---|---|
| Intersection | 64% | 51% |
| Non-intersection | 19% | 35% |
| Intersection Related | 6% | 9% |
| Driveway | 9% | 5% |
| In Alley | 2% | 0% |
Vehicle Action
Table 2 identifies the vehicle action during the crash. Most crashes involve vehicles traveling straight, including 71 percent of pedestrian collisions and 53 percent of bicyclist collisions. The single most common vehicle action involved a vehicle going straight away from an intersection, representing 45 percent of all pedestrian collisions. Vehicles turning left or right at intersections accounted for 11 percent of pedestrian crashes and 27 percent of bicyclist crashes.
Table 2 – Summary of Location and Vehicle Action
| Vehicle Action | Location: Driveway Access | Location: Intersection | Location: Intersection Relation | Location: Non-Intersection | Location: Other | Location: Total |
|---|---|---|---|---|---|---|
| Pedestrian Crashes | ||||||
| Going Straight | 2% | 16% | 3% | 17% | 1% | 38% |
| Making Left Turn | 1% | 14% | 1% | 0% | 0% | 16% |
| Making Right Turn | 1% | 10% | 2% | 0% | 0% | 13% |
| Other | 1% | 11% | 2% | 18% | 1% | 33% |
| Total | 5% | 51% | 8% | 35% | 1% | 100% |
| Bicycle Crashes | ||||||
| Going Straight | 2% | 34% | 3% | 10% | 1% | 51% |
| Making Left Turn | 3% | 11% | 1% | 1% | 0% | 16% |
| Making Right Turn | 3% | 11% | 1% | 1% | 0% | 16% |
| Other | 2% | 7% | 1% | 2% | 1% | 17% |
| Total | 10% | 64% | 6% | 19% | 2% | 100% |
Opportunities For Improved Crash Data
The crash data provides only limited information to understand the nature of crashes involving pedestrians and bicyclists. Below are three categories that could be improved or added to the data to provide greater clarity and increase the ability to match appropriate countermeasures with particular safety issues.
- Category 1: Change and increase the use of the contributing factor field for collision reports. More than 40 percent of crashes listed the contributing factor as None while another 15 percent listed the factor as Unknown. Common contributing factors are Careless/Prohibited Driving and Failure to Yield, which offer little insight.
- Category 2: Increase the data points of bicycle/pedestrian crash data to include actions (e.g. pedestrian crossing at mid-block, pedestrian crossing at unmarked location, bicyclist taking left through intersection, etc.) that would offer more information.
- Category 3: Collect additional data, such as demographic information, to understand disproportionate impacts or concerns.
Figures 11 and 12 show the location of reported bicyclist and pedestrian crashes as well as the locations of fatalities within the MPO boundary.
Figure 11: Bicycle Crash Map: 2017–2021 Data
Figure 12. Pedestrian Crash Map—2017–2021 Data
